Physical Sciences and Mathematics Commons^™

Electrochemical Performance Of Porous Ceramic Supported Tubular Solid Oxide Electrolysis Cell, Heng-Ji Wang, Wen-Guo Chen, Zhou-Yi Quan, Kai Zhao, Yi-Fei Sun, Min Chen, Ogenko Volodymyr

Journal of Electrochemistry

Solid oxide electrolysis cell (SOEC) is an efficient and clean energy conversion technology that can utilize electricity obtained from renewable resources, such as solar, wind, and geothermal energy to electrolyze water and produce hydrogen. The conversion of abundant intermittent energy to hydrogen energy would facilitate the efficient utilization of energy resources. SOEC is an all-ceramic electrochemical cell that operates in the intermediate to high temperature range of 500–750 ℃. Compared with traditional low temperature electrolysis technology (e.g., alkaline or proton exchange membrane cells operating at ~100 ℃), the high-temperature SOEC can increase the electrolysis efficiency from 80% to ~100%, providing …

Nitrogen-Doped Graphite Felt On The Performance Of Aqueous Quinone-Based Redox Flow Batteries, Heng Zhang, Li-Xing Xia, Shan Jiang, Fu-Zhi Wang, Zhan-Ao Tan

Journal of Electrochemistry

Modification of electrode is vitally important for achieving high energy efficiency in aqueous quinone-based redox flow batteries (AQRFBs). The modification of graphite felt (GF) was carried out by means of urea hydrothermal reaction, and simultaneously, the effects of hydrothermal reaction time on the functional groups and surface structure of nitrogen-doped graphite felt were studied. The surface morphology and defect, element content and surface chemical state of the modified electrode were characterized by scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) test, Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). The electrochemical performance of the modified electrodes was evaluated by cyclic voltammetry, electrochemical impedance …

An In-Situ Raman Spectroscopic Study On The Interfacial Process Of Carbonate-Based Electrolyte On Nanostructured Silver Electrode, Yu Gu, Yuan-Fei Hu, Wei-Wei Wang, En-Ming You, Shuai Tang, Jian-Jia Su, Jun Yi, Jia-Wei Yan, Zhong-Qun Tian, Bing-Wei Mao

Journal of Electrochemistry

The solid-electrolyte interphase (SEI) plays a key role in anodes for rechargeable lithium-based battery technologies. However, a thorough understanding in the mechanisms of SEI formation and evolution remains a major challenge, hindering the rapid development and wide applications of Li-based batteries. Here, we devise a borrowing surface-enhanced Raman scattering (SERS) activity strategy by utilizing a size optimized Ag nanosubstrate to in-situ monitor the formation and evolution of SEI, as well as its structure and chemistry in an ethylene carbonate-based electrolyte. To ensure a reliable in-situ SERS investigation, we designed a strict air-tight Raman cell with a three-electrode configuration. Based on …

Solar-Powered Microgrids In Northern California: An Opportunity For Resilience, Marina Riddle

Master's Projects and Capstones

Planned and unplanned power outages have been increasing in frequency and duration, negatively impacting all public sectors, and threatening public safety. These outages are deadly to those who rely on medical devices. As climate change-fueled extreme weather events (wildfires, earthquakes, storms, etc.) also increase in frequency, our electrical grid must be prepared to bounce back. Microgrids provide necessary redundancy and reliability. Through a novel GIS suitability analysis, based on solar radiation, land use type, local energy demand, distance to transmission lines, distance to roads, and slope, optimal locations for solar-powered microgrids throughout Northern California were determined. The counties of Fresno, …

A Map-Algebra-Inspired Approach For Interacting With Wireless Sensor Networks, Cyber-Physical Systems Or Internet Of Things, David Almeida

Electronic Theses and Dissertations

The typical approach for consuming data from wireless sensor networks (WSN) and Internet of Things (IoT) has been to send data back to central servers for processing and analysis. This thesis develops an alternative strategy for processing and acting on data directly in the environment referred to as Active embedded Map Algebra (AeMA). Active refers to the near real time production of data, and embedded refers to the architecture of distributed embedded sensor nodes. Network macroprogramming, a style of programming adopted for wireless sensor networks and IoT, addresses the challenges of coordinating the behavior of multiple connected devices through a …

Static And Dynamic State Estimation Applications In Power Systems Protection And Control Engineering, Ibukunoluwa Olayemi Korede

Doctoral Dissertations

The developed methodologies are proposed to serve as support for control centers and fault analysis engineers. These approaches provide a dependable and effective means of pinpointing and resolving faults, which ultimately enhances power grid reliability. The algorithm uses the Least Absolute Value (LAV) method to estimate the augmented states of the PCB, enabling supervisory monitoring of the system. In addition, the application of statistical analysis based on projection statistics of the system Jacobian as a virtual sensor to detect faults on transmission lines. This approach is particularly valuable for detecting anomalies in transmission line data, such as bad data or …

Diverse Impacts Of Commercial Ev Charging Load Infrastructure On Electric Power Grid, Antonio Avila

Open Access Theses & Dissertations

With the rising prominence of electric vehicles (EVs) in the transportation sector, this thesis delves into the critical nexus between commercial EVs, charging infrastructure, and their consequential impacts on the power grid. As commercial EVs, particularly medium and heavy-duty variants, gain traction as viable alternatives in the commercial transportation landscape, understanding the intricacies of their charging requirements becomes paramount. This thesis critically examines the technological and logistical dimensions of the charging infrastructure for supporting commercial EVs, evaluating the consequential implications on the power grid and proposing strategies for mitigation through the utilization of Distributed Energy Resources (DERs). In tandem with …

Initiation Criteria For The Onset Of Geomagnetic Substorms Based On Auroral Observations And Electrojet Current Signatures, Mayowa Michael Kayode-Adeoye

<strong> Theses and Dissertations </strong>

In recent years, several substorm onset criteria have been developed, either from auroral observations (many authors) or from auroral electrojet properties such as those described by (Forsyth et al., 2015; Maimaiti et al., 2019; Newell & Gjerloev, 2011; Partamies et al., 2011) The different criteria are being investigated using a low order physics model of the magnetosphere called WINDMI (Spencer et al., 2009) and inferences are being made in line with the WINDMI model. The model variables will be compared with the criteria for substorm onset proposed by examining the SML index.

The WINDMI model uses solar wind and IMF …

Hpc-Enabled Fast And Configurable Dynamic Simulation, Analysis, And Learning For Complex Power System Adaptation And Control, Cong Wang

All Dissertations

This dissertation presents an HPC-enabled fast and configurable dynamic simulation, analysis, and learning framework for complex power system adaptation and control. Dynamic simulation for a large transmission system comprising thousands of buses and branches implies the latency of complicated numerical computations. However, faster-than-real-time execution is often required to provide timely support for power system planning and operation. The traditional approaches for speeding up the simulation demand extensive computing facilities such as CPU-based multi-core supercomputers, resulting in heavily resource-dependent solutions. In this work, by coupling the Message Passing Interface (MPI) protocol with an advanced heterogeneous programming environment, further acceleration can be …

Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt

All Dissertations

Remotely actuated microscale swimming robots have the potential to revolutionize many aspects of biomedicine. However, for the longterm goals of this field of research to be achievable, it is necessary to develop modelling, simulation, and control strategies which effectively and efficiently account for not only the motion of individual swimmers, but also the complex interactions of such swimmers with their environment including other nearby swimmers, boundaries, other cargo and passive particles, and the fluid medium itself. The aim of this thesis is to study these problems in simulation from the perspective of controls and dynamical systems, with a particular focus …

Vertical Free-Swinging Photovoltaic Racking Energy Modeling: A Novel Approach To Agrivoltaics, Koami Soulemane Hayibo, Joshua M. Pearce

Electrical and Computer Engineering Publications

To enable lower-cost building materials, a free-swinging bifacial vertical solar photovoltaic (PV) rack has been proposed, which complies with Canadian building codes and is the lowest capital-cost agrivoltaics rack. The wind force applied to the free-swinging PV, however, causes it to have varying tilt angles depending on the wind speed and direction. No energy performance model accurately describes such a system. To provide a simulation model for the free-swinging PV, where wind speed and direction govern the array tilt angle, this study builds upon the open-source System Advisor Model (SAM) using Python. After the SAM python model is validated, a …

Enhanced Privacy-Enabled Face Recognition Using Κ-Identity Optimization, Ryan Karl

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Facial recognition is becoming more and more prevalent in the daily lives of the common person. Law enforcement utilizes facial recognition to find and track suspects. The newest smartphones have the ability to unlock using the user's face. Some door locks utilize facial recognition to allow correct users to enter restricted spaces. The list of applications that use facial recognition will only increase as hardware becomes more cost-effective and more computationally powerful. As this technology becomes more prevalent in our lives, it is important to understand and protect the data provided to these companies. Any data transmitted should be encrypted …

Use Of Digital Twins To Mitigate Communication Failures In Microgrids, Andrew Eggebeen

Theses and Dissertations

This work investigates digital twin (DT) applications for electric power system (EPS) resilience. A novel DT architecture is proposed consisting of a physical twin, a virtual twin, an intelligent agent, and data communications. Requirements for the virtual twin are identified. Guidelines are provided for generating, capturing, and storing data to train the intelligent agent. The relationship between the DT development process and an existing controller hardware-in-the-loop (CHIL) process is discussed. To demonstrate the proposed DT architecture and development process, a DT for a battery energy storage system (BESS) is created based on the simulation of an industrial nanogrid. The creation …

Electronic Note-String Detector, Gavin Garcia-Rossi, Tommy Smail

Electrical Engineering

As the virtual space has become a dominant part of everyone’s day-to-day lives, many normal face-to-face interactions and services have not yet been facilitated by adapting technology. One of these prevailing areas is music lessons. Over Zoom meetings, or other virtual platforms, it is tremendously challenging to teach students. These challenges include recognizing student mistakes audibly and visually, and being able to give confident feedback on the incorrect notes played by learning musicians. Without having to delve into improving the complex systems that would be required to improve audio, video, and connection quality of these connections, we have another solution …

A Design Strategy To Improve Machine Learning Resiliency Of Physically Unclonable Functions Using Modulus Process, Yuqiu Jiang

Theses and Dissertations

Physically unclonable functions (PUFs) are hardware security primitives that utilize non-reproducible manufacturing variations to provide device-specific challenge-response pairs (CRPs). Such primitives are desirable for applications such as communication and intellectual property protection. PUFs have been gaining considerable interest from both the academic and industrial communities because of their simplicity and stability. However, many recent studies have exposed PUFs to machine-learning (ML) modeling attacks. To improve the resilience of a system to general ML attacks instead of a specific ML technique, a common solution is to improve the complexity of the system. Structures, such as XOR-PUFs, can significantly increase the nonlinearity …

Robust And Uncertainty-Aware Image Classification Using Bayesian Vision Transformer Model, Fazlur Rahman Bin Karim

Theses and Dissertations

Transformer Neural Networks have emerged as the predominant architecture for addressing a wide range of Natural Language Processing (NLP) applications such as machine translation, speech recognition, sentiment analysis, text anomaly detection, etc. This noteworthy achievement of Transformer Neural Networks in the NLP field has sparked a growing interest in integrating and utilizing Transformer models in computer vision tasks. The Vision Transformer (ViT) model efficiently captures long-range dependencies by employing a self-attention mechanism to transform different image data into meaningful, significant representations. Recently, the Vision Transformer (ViT) has exhibited incredible performance in solving image classification problems by utilizing ViT models, thereby …

Ensuring Non-Repudiation In Long-Distance Constrained Devices, Ethan Blum

Honors Theses

Satellite communication is essential for the exploration and study of space. Satellites allow communications with many devices and systems residing in space and on the surface of celestial bodies from ground stations on Earth. However, with the rise of Ground Station as a Service (GsaaS), the ability to efficiently send action commands to distant satellites must ensure non-repudiation such that an attacker is unable to send malicious commands to distant satellites. Distant satellites are also constrained devices and rely on limited power, meaning security on these devices is minimal. Therefore, this study attempted to propose a novel algorithm to allow …

Accelerating Machine Learning Inference For Satellite Component Feature Extraction Using Fpgas., Andrew Ekblad

Theses and Dissertations

Running computer vision algorithms requires complex devices with lots of computing power, these types of devices are not well suited for space deployment. The harsh radiation environment and limited power budgets have hindered the ability of running advanced computer vision algorithms in space. This problem makes running an on-orbit servicing detection algorithm very difficult. This work proposes using a low powered FPGA to accelerate the computer vision algorithms that enable satellite component feature extraction. This work uses AMD/Xilinx’s Zynq SoC and DPU IP to run model inference. Experiments in this work centered around improving model post processing by creating implementations …

Qasm-To-Hls: A Framework For Accelerating Quantum Circuit Emulation On High-Performance Reconfigurable Computers, Anshul Maurya

Theses and Dissertations

High-performance reconfigurable computers (HPRCs) make use of Field-Programmable Gate Arrays (FPGAs) for efficient emulation of quantum algorithms. Generally, algorithm-specific architectures are implemented on the FPGAs and there is very little flexibility. Moreover, mapping a quantum algorithm onto its equivalent FPGA emulation architecture is challenging. In this work, we present an automation framework for converting quantum circuits to their equivalent FPGA emulation architectures. The framework processes quantum circuits represented in Quantum Assembly Language (QASM) and derives high-level descriptions of the hardware emulation architectures for High-Level Synthesis (HLS) on HPRCs. The framework generates the code for a heterogeneous architecture consisting of a …

Travel Time Theory For Traffic Conservation Laws With Applications, Sergio Contreras

UNLV Theses, Dissertations, Professional Papers, and Capstones

Travel time is an important concept in various intelligent transportation system (ITS) applications. The concept is used in a wide array of applications, such as system planning, system performance, and optimization. Reducing the time required to travel between different points on a network is an important goal. Benefits include reducing time wasted in traveling, and keeping travelers satisfied. Thus, studying and reducing travel time in ITS is beneficial in different applications.

The classic density-based Lighthill Whitman Richards (LWR) equation for modeling traffic flow is the starting point in this dissertation. A more recent travel time dynamics function built on top …

Implementation Of Adas And Autonomy On Unlv Campus, Zillur Rahman

UNLV Theses, Dissertations, Professional Papers, and Capstones

The integration of Advanced Driving Assistance Systems (ADAS) and autonomous driving functionalities into contemporary vehicles has notably surged, driven by the remarkable progress in artificial intelligence (AI). These AI systems, capable of learning from real-world data, now exhibit the capability to perceive their surroundings via a suite of sensors, create optimal routes from source to destination, and execute vehicle control akin to a human driver.

Within the context of this thesis, we undertake a comprehensive exploration of three distinct yet interrelated ADAS and Autonomy projects. Our central objective is the implementation of autonomous driving(AD) technology at UNLV campus, culminating in …

On The Effect Of Emotion Identification From Limited Translated Text Samples Using Computational Intelligence, Madiha Tahir, Zahid Halim, Muhmmad Waqas, Shanshan Tu

Research outputs 2022 to 2026

Emotion identification from text data has recently gained focus of the research community. This has multiple utilities in an assortment of domains. Many times, the original text is written in a different language and the end-user translates it to her native language using online utilities. Therefore, this paper presents a framework to detect emotions on translated text data in four different languages. The source language is English, whereas the four target languages include Chinese, French, German, and Spanish. Computational intelligence (CI) techniques are applied to extract features, dimensionality reduction, and classification of data into five basic classes of emotions. Results …

A Practical Low-Dimensional Feature Vector Generation Method Based On Wavelet Transform For Psychophysiological Signals, Erdem Erkan, Yasemi̇n Erkan

Turkish Journal of Electrical Engineering and Computer Sciences

High-dimensional feature vectors entail computational cost and computational complexity. However, a successful classification can be obtained with an optimally sized feature vector consisting of distinctive features. With the widespread use of the internet and mobile devices, the need for systems with low computational costs is increasing day by day. In this study, starting from the idea that each motor imagery is represented as a subject-specific pattern in the brain, we propose a new and practical method that can generate a low-dimensional feature vector based on wavelet transform. The feature vector is obtained from the correlation between each trial and each …

Fuzzycsampling: A Hybrid Fuzzy C-Means Clustering Sampling Strategy For Imbalanced Datasets, Abdullah Maraş, Çi̇ğdem Erol

Turkish Journal of Electrical Engineering and Computer Sciences

Classification model with imbalanced datasets is recently one of the most researched areas in machine learning applications since they induce to the emergence of low-performing machine learning models. The imbalanced datasets occur if target variables have an uneven number of examples in a dataset. The most prevalent solutions to imbalanced datasets can be categorized as data preprocessing, ensemble techniques, and cost-sensitive learning. In this article, we propose a new hybrid approach for binary classification, named FuzzyCSampling, which aims to increase model performance by ensembling fuzzy c-means clustering and data sampling solutions. This article compares the proposed approaches' results not only …

Feature Selection Optimization With Filtering And Wrapper Methods: Two Disease Classification Cases, Serhat Ati̇k, Tuğba Dalyan

Turkish Journal of Electrical Engineering and Computer Sciences

Discarding the less informative and redundant features helps to reduce the time required to train a learning algorithm and the amount of storage required, improving the learning accuracy as well as the quality of results. In this study, we present different feature selection approaches to address the problem of disease classification based on the Parkinson and Cardiac Arrhythmia datasets. For this purpose, first we utilize three filtering algorithms including the Pearson correlation coefficient, Spearman correlation coefficient, and relief. Second, metaheuristic algorithms are compared to find the most informative subset of the features to obtain better classification accuracy. As a final …

New Modified Carrier-Based Level-Shifted Pwm Control For Npc Rectifiers Considered For Implementation In Ev Fast Chargers, Merve Mollahasanoğlu, Hakki Mollahasanoğlu, Hali̇l İbrahi̇m Okumuş

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the aim is to evaluate three-phase (3?) AC/DC neutral point-clamped (NPC) power factor corrected (PFC) multilevel converter performance for electric vehicle (EV) fast chargers. Power factor correction for EV fast chargers is very important in terms of efficient power usage and charger compatibility with the grid. Multilevel converters improve charging efficiency, reduce voltage stresses on components, minimize electromagnetic interference, and support high power capabilities. For this reason, multilevel converters with the PFC feature contribute to the reliable and effective operation of the fast-charging infrastructure. Rectifier analysis is tested with extensive simulations using a new modified carrier-based level-shifted …

A Comparative Study Of Yolo Models And A Transformer-Based Yolov5 Model For Mass Detection In Mammograms, Damla Coşkun, Dervi̇ş Karaboğa, Alper Baştürk, Bahri̇ye Akay, Özkan Ufuk Nalbantoğlu, Serap Doğan, İshak Paçal, Meryem Altin Karagöz

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is a prevalent form of cancer across the globe, and if it is not diagnosed at an early stage it can be life-threatening. In order to aid in its diagnosis, detection, and classification, computer-aided detection (CAD) systems are employed. You Only Look Once (YOLO)-based CAD algorithms have become very popular owing to their highly accurate results for object detection tasks in recent years. Therefore, the most popular YOLO models are implemented to compare the performance in mass detection with various experiments on the INbreast dataset. In addition, a YOLO model with an integrated Swin Transformer in its backbone …

Machine Learning Based Bioinformatics Analysis Of Intron Usage Alterations And Metabolic Regulation In Adipose Browning, Hamza Umut Karakurt, Pinar Pi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Adipose tissue is the major energy depot of the body and is considered an endocrine organ. Adipose tissue involves many different cell types, first and foremost, the adipocytes. White adipose cells that store fat and brown adipocytes that take part in lipid oxidation and heat generation are the most common cell types in adipose tissue. Even though brown adipocytes which have a high number of mitochondria and high fat-burning capacity are rare in adults, they are abundant in newborns and rodents. White adipocytes can gain a temporal brown-like character with a process called browning, which can be induced with cold …

Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen

Electrical and Computer Engineering ETDs

These days large volumes of data can be recorded and manipulated with relative ease. If valuable information can be extracted from them, these vast amounts of data can be a rich resource not just for the digital economy but also for scientific discovery and development of technology. When it comes to deriving valuable information from data, Machine Learning (ML) emerges as the key solution. To unlock the potential benefits of ML to science and technology, extensive research is needed to explore what algorithms are suitable and how they can be applied.

To shine light on various ways that ML can …

Charge Transfer Evaluation In Solid Insulating Materials Encapsulating The Gaseous Voids Of Submillimeter Dimensions Using Transmission Line Method, Amin Shamsi, Alireza Ganjovi, Amir Abas Shayegani Akmal

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, using a lumped RC circuit model which is based on transmission line modeling (TLM) method, the charge transfer in a solid insulating system encapsulating a gaseous void of submillimeter dimensions is evaluated. Here, both the dielectric material and gaseous void are considered simultaneously as a transmission line. The transmission line includes the capacitive and resistance elements and, the obtained circuit equations were coupled with the continuity and kinetic energy equations for charged species along with Poisson's equation. These equations are solved via 4th order Runge-Kutta method and, the electric field and potential, density of all the charged …